top-down-tutorial.bib

@manual{bastan2020exactextractr,
    title = {{exactextractr}: Fast Extraction from Raster Datasets using Polygons},
    author = {{Daniel Baston}},
    year = {2020},
    note = {R package version 0.5.1},
    url = {https://CRAN.R-project.org/package=exactextractr},
  }

@manual{bondarenko2018,
	title = {{wpgpRFPMS: WorldPop Random Forests population modelling R scripts, version 0.1.0}},
	author = {{Bondarenko}, {Maksym} and {Nieves}, {Jeremiah} and {Sorichetta}, {Alessandro} and {Stevens}, {Forrest R} and {Gaughan}, {Andrea E} and {Tatem}, {Andrew} and {others}, {}},
	year = {2018},
	publisher = {WorldPop, University of Southampton},
	doi={10.5258/SOTON/WP00665},
	url={https://github.com/wpgp/wpgpRFPMS}
}

@article{breiman2001,
	title = {Random forests},
	author = {{Breiman}, {Leo}},
	year = {2001},
	journal = {Machine learning},
	pages = {5--32},
	volume = {45},
	number = {1},
	note = {ISBN: 0885-6125},
	publisher = {Springer},
	doi = {10.1023/A:1010933404324}
}

@article{genuer2010,
	title = {Variable selection using random forests},
	author = {{Genuer}, {Robin} and {Poggi}, {Jean-Michel} and {Tuleau-Malot}, {Christine}},
	year = {2010},
	date = {2010},
	journal = {Pattern recognition letters},
	pages = {2225-2236},
	volume = {31},
	number = {14},
	publisher = {Elsevier},
	doi = {10.1016/j.patrec.2010.03.014}
}

@Manual{hijmans2020raster,
    title = {{raster}: Geographic Data Analysis and Modeling},
    author = {Robert J. Hijmans},
    year = {2020},
    note = {R package version 3.3-13},
    url = {https://CRAN.R-project.org/package=raster},
  }
  
@manual{ibge2019brazilian,
  author = {{IBGE}},
  year = {2019},
  title = {Brazilian Territorial Division, 2019 Edition},
  publisher = {{Brazilian Institute of Geography and Environment (IBGE)}},
  url = {https://www.ibge.gov.br/en/geosciences/territorial-organization/regional-division/23708-brazilian-territorial-division.html?=&t=o-que-e}
}

@manual{ibge2020meshes,
  author = {{IBGE}},
  year = {2020},
  title = {Meshes of census sectors intra-municipal divisions},
  publisher = {{Brazilian Institute of Geography and Environment (IBGE)}},
  url = {http://geoftp.ibge.gov.br/organizacao_do_territorio/malhas_territoriais/malhas_de_setores_censitarios__divisoes_intramunicipais/2019/Malha_de_setores_(shp)_Brasil/}
}

@manual{ibge2020population,
  author = {{IBGE}},
  year = {2020},
  title = {Population Estimates - Tables 2020},
  publisher = {{Brazilian Institute of Geography and Environment (IBGE)}},
  url = {https://www.ibge.gov.br/en/statistics/social/18448-population-estimates.html?=&t=resultados}
}

@Article{law2018,
    title = {Classification and Regression by randomForest},
    author = {Andy Liaw and Matthew Wiener},
    journal = {R News},
    year = {2002},
    volume = {2},
    number = {3},
    pages = {18-22},
    url = {https://cran.r-project.org/package=randomForest}
  }

@article{lloyd2019global,
  title={Global spatio-temporally harmonised datasets for producing high-resolution gridded population distribution datasets},
  author={Lloyd, Christopher T and Chamberlain, Heather and Kerr, David and Yetman, Greg and Pistolesi, Linda and Stevens, Forrest R and Gaughan, Andrea E and Nieves, Jeremiah J and Hornby, Graeme and MacManus, Kytt and others},
  journal={Big earth data},
  volume={3},
  number={2},
  pages={108--139},
  year={2019},
  publisher={Taylor \& Francis}
}

@article{lloyd2017high,
  title={High resolution global gridded data for use in population studies},
  author={Lloyd, Christopher T and Sorichetta, Alessandro and Tatem, Andrew J},
  journal={Scientific data},
  volume={4},
  number={1},
  pages={1--17},
  year={2017},
  publisher={Nature Publishing Group}
}

@Manual{microsoft2020doParallel,
    title = {doParallel: Foreach Parallel Adaptor for the 'parallel' Package},
    author = {Microsoft Corporation and Steve Weston},
    year = {2020},
    note = {R package version 1.0.16},
    url = {https://CRAN.R-project.org/package=doParallel},
}
  
@Article{pebesma2018simple,
    author = {Edzer Pebesma},
    title = {{Simple Features for R: Standardized Support for Spatial Vector Data}},
    year = {2018},
    journal = {{The R Journal}},
    doi = {10.32614/RJ-2018-009},
    url = {https://doi.org/10.32614/RJ-2018-009},
    pages = {439--446},
    volume = {10},
    number = {1},
  }
  
@Manual{r2020r,
    title = {R: A Language and Environment for Statistical Computing},
    author = {{R Core Team}},
    organization = {R Foundation for Statistical Computing},
    address = {Vienna, Austria},
    year = {2020},
    url = {https://www.R-project.org/},
  }

@inproceedings{robnik-ikonja2004,
  title={Improving random forests},
  author={Robnik-{\v{S}}ikonja, Marko},
  booktitle={European conference on machine learning},
  pages={359--370},
  year={2004},
  organization={Springer},
  doi={10.1007/978-3-540-30115-8_34}
}

@article{sorichetta2015,
	title = {{High-resolution gridded population datasets for Latin America and the Caribbean in 2010, 2015, and 2020}},
	author = {{Sorichetta}, {Alessandro} and {Hornby}, {Graeme M.} and {Stevens}, {Forrest R.} and {Gaughan}, {Andrea E.} and {Linard}, {Catherine} and {Tatem}, {Andrew J.}},
	year = {2015},
	journal = {Scientific Data},
	pages = {1--12},
	volume = {2},
	number = {1},
	doi = {10.1038/sdata.2015.45},
	publisher = {Nature Publishing Group}
}

@article{stevens2015,
	title = {Disaggregating Census Data for Population Mapping Using Random Forests with Remotely-Sensed and Ancillary Data},
	author = {{Stevens}, {Forrest R.} and {Gaughan}, {Andrea E.} and {Linard}, {Catherine} and {Tatem}, {Andrew J.}},
	year = {2015},
	journal = {PLOS ONE},
	pages = {e0107042},
	volume = {10},
	number = {2},
	doi = {10.1371/journal.pone.0107042},
}

@manual{worldpop2018geospatial,
  author = {WorldPop and CIESIN},
  year = {2018},
  title = {{Geospatial covariate data layers: VIIRS night-time lights (2012-216), Brazil}},
  publisher = {WorldPop, University of Southampton},
  doi = {10.5258/SOTON/WP00644},
  url = {ftp://ftp.worldpop.org/GIS/Covariates/Global_2000_2020/BRA/VIIRS/},
  note = {Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076)}
}

@manual{worldpop2018mastergrid,
  author = {WorldPop and CIESIN},
  year = {2018},
  title = {{Administrative Areas: National Boundaries, Brazil}},
  publisher = {WorldPop, University of Southampton},
  doi = {10.5258/SOTON/WP00651},
  url = {ftp://ftp.worldpop.org/GIS/Mastergrid/Global_2000_2020/BRA/L0/},
  note = {Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076)}
}